Overview

Brought to you by YData

Dataset statistics

Number of variables19
Number of observations1031175
Missing cells72276
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 GiB
Average record size in memory1.2 KiB

Variable types

Numeric5
Text10
URL3
Categorical1

Alerts

Language is highly imbalanced (78.5%) Imbalance
city has 14103 (1.4%) missing values Missing
state has 22798 (2.2%) missing values Missing
country has 35374 (3.4%) missing values Missing
Unnamed: 0 is uniformly distributed Uniform
Unnamed: 0 has unique values Unique
rating has 647323 (62.8%) zeros Zeros

Reproduction

Analysis started2025-02-26 11:12:58.857438
Analysis finished2025-02-26 11:14:28.434495
Duration1 minute and 29.58 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

Unnamed: 0
Real number (ℝ)

Uniform  Unique 

Distinct1031175
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean515587
Minimum0
Maximum1031174
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size7.9 MiB
2025-02-26T11:14:28.592249image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile51558.7
Q1257793.5
median515587
Q3773380.5
95-th percentile979615.3
Maximum1031174
Range1031174
Interquartile range (IQR)515587

Descriptive statistics

Standard deviation297674.73
Coefficient of variation (CV)0.57735111
Kurtosis-1.2
Mean515587
Median Absolute Deviation (MAD)257794
Skewness1.4842383 × 10-15
Sum5.3166042 × 1011
Variance8.8610243 × 1010
MonotonicityStrictly increasing
2025-02-26T11:14:28.779551image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1
 
< 0.1%
687455 1
 
< 0.1%
687442 1
 
< 0.1%
687443 1
 
< 0.1%
687444 1
 
< 0.1%
687445 1
 
< 0.1%
687446 1
 
< 0.1%
687447 1
 
< 0.1%
687448 1
 
< 0.1%
687449 1
 
< 0.1%
Other values (1031165) 1031165
> 99.9%
ValueCountFrequency (%)
0 1
< 0.1%
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
ValueCountFrequency (%)
1031174 1
< 0.1%
1031173 1
< 0.1%
1031172 1
< 0.1%
1031171 1
< 0.1%
1031170 1
< 0.1%
1031169 1
< 0.1%
1031168 1
< 0.1%
1031167 1
< 0.1%
1031166 1
< 0.1%
1031165 1
< 0.1%

user_id
Real number (ℝ)

Distinct92107
Distinct (%)8.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean140594.37
Minimum2
Maximum278854
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 MiB
2025-02-26T11:14:28.953497image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile14422
Q170415
median141210
Q3211426
95-th percentile264331.7
Maximum278854
Range278852
Interquartile range (IQR)141011

Descriptive statistics

Standard deviation80524.435
Coefficient of variation (CV)0.57274294
Kurtosis-1.2265592
Mean140594.37
Median Absolute Deviation (MAD)70616
Skewness-0.023981499
Sum1.449774 × 1011
Variance6.4841846 × 109
MonotonicityNot monotonic
2025-02-26T11:14:29.147061image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11676 11144
 
1.1%
198711 6456
 
0.6%
153662 5814
 
0.6%
98391 5779
 
0.6%
35859 5646
 
0.5%
212898 4290
 
0.4%
278418 3996
 
0.4%
76352 3329
 
0.3%
110973 2971
 
0.3%
235105 2943
 
0.3%
Other values (92097) 978807
94.9%
ValueCountFrequency (%)
2 1
 
< 0.1%
8 17
< 0.1%
9 3
 
< 0.1%
10 1
 
< 0.1%
12 1
 
< 0.1%
14 4
 
< 0.1%
16 2
 
< 0.1%
17 7
< 0.1%
19 1
 
< 0.1%
20 1
 
< 0.1%
ValueCountFrequency (%)
278854 8
 
< 0.1%
278852 1
 
< 0.1%
278851 23
 
< 0.1%
278849 4
 
< 0.1%
278846 1
 
< 0.1%
278844 2
 
< 0.1%
278843 60
< 0.1%
278838 6
 
< 0.1%
278836 1
 
< 0.1%
278832 3
 
< 0.1%
Distinct22480
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size81.6 MiB
2025-02-26T11:14:29.447324image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length69
Median length59
Mean length25.180217
Min length3

Characters and Unicode

Total characters25965210
Distinct characters91
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8399 ?
Unique (%)0.8%

Sample

1st rowstockton, california, usa
2nd rowtimmins, ontario, canada
3rd rowottawa, ontario, canada
4th rown/a, n/a, n/a
5th rowsudbury, ontario, canada
ValueCountFrequency (%)
usa 746584
 
21.1%
california 107540
 
3.0%
canada 99471
 
2.8%
new 87325
 
2.5%
n/a 44526
 
1.3%
texas 44185
 
1.2%
ontario 41505
 
1.2%
york 37561
 
1.1%
virginia 36906
 
1.0%
florida 34285
 
1.0%
Other values (14214) 2260285
63.8%
2025-02-26T11:14:29.902258image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3266628
12.6%
2509400
 
9.7%
, 2065908
 
8.0%
n 1904641
 
7.3%
s 1851542
 
7.1%
i 1701268
 
6.6%
o 1549232
 
6.0%
e 1448319
 
5.6%
r 1307523
 
5.0%
u 1210337
 
4.7%
Other values (81) 7150412
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25965210
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3266628
12.6%
2509400
 
9.7%
, 2065908
 
8.0%
n 1904641
 
7.3%
s 1851542
 
7.1%
i 1701268
 
6.6%
o 1549232
 
6.0%
e 1448319
 
5.6%
r 1307523
 
5.0%
u 1210337
 
4.7%
Other values (81) 7150412
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25965210
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3266628
12.6%
2509400
 
9.7%
, 2065908
 
8.0%
n 1904641
 
7.3%
s 1851542
 
7.1%
i 1701268
 
6.6%
o 1549232
 
6.0%
e 1448319
 
5.6%
r 1307523
 
5.0%
u 1210337
 
4.7%
Other values (81) 7150412
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25965210
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3266628
12.6%
2509400
 
9.7%
, 2065908
 
8.0%
n 1904641
 
7.3%
s 1851542
 
7.1%
i 1701268
 
6.6%
o 1549232
 
6.0%
e 1448319
 
5.6%
r 1307523
 
5.0%
u 1210337
 
4.7%
Other values (81) 7150412
27.5%

age
Real number (ℝ)

Distinct93
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.429017
Minimum5
Maximum99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 MiB
2025-02-26T11:14:30.092973image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile22
Q131
median34.7439
Q341
95-th percentile57
Maximum99
Range94
Interquartile range (IQR)10

Descriptive statistics

Standard deviation10.353539
Coefficient of variation (CV)0.28421133
Kurtosis1.2230354
Mean36.429017
Median Absolute Deviation (MAD)4.7438999
Skewness0.76586581
Sum37564691
Variance107.19578
MonotonicityNot monotonic
2025-02-26T11:14:30.284220image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.74389988 282595
27.4%
33 32864
 
3.2%
29 30648
 
3.0%
30 27202
 
2.6%
32 26492
 
2.6%
36 26097
 
2.5%
28 25967
 
2.5%
31 25965
 
2.5%
34 25893
 
2.5%
38 22396
 
2.2%
Other values (83) 505056
49.0%
ValueCountFrequency (%)
5 159
 
< 0.1%
6 14
 
< 0.1%
7 148
 
< 0.1%
8 542
 
0.1%
9 2056
0.2%
10 227
 
< 0.1%
11 513
 
< 0.1%
12 747
 
0.1%
13 1243
 
0.1%
14 3206
0.3%
ValueCountFrequency (%)
99 5
 
< 0.1%
98 1
 
< 0.1%
97 127
< 0.1%
96 13
 
< 0.1%
95 1
 
< 0.1%
94 1
 
< 0.1%
93 34
 
< 0.1%
92 47
 
< 0.1%
90 45
 
< 0.1%
89 2
 
< 0.1%

isbn
Text

Distinct270170
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size65.9 MiB
2025-02-26T11:14:30.646493image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length13
Median length10
Mean length10.000012
Min length10

Characters and Unicode

Total characters10311762
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique145658 ?
Unique (%)14.1%

Sample

1st row0195153448
2nd row0002005018
3rd row0002005018
4th row0002005018
5th row0002005018
ValueCountFrequency (%)
0971880107 2502
 
0.2%
0316666343 1295
 
0.1%
0385504209 883
 
0.1%
0060928336 732
 
0.1%
0312195516 723
 
0.1%
044023722x 649
 
0.1%
067976402x 618
 
0.1%
0142001740 615
 
0.1%
0671027360 586
 
0.1%
0446672211 585
 
0.1%
Other values (269853) 1021990
99.1%
2025-02-26T11:14:31.185663image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1932130
18.7%
4 1082823
10.5%
1 1062075
10.3%
5 1038144
10.1%
3 1034312
10.0%
2 876562
8.5%
7 861219
8.4%
6 841552
8.2%
8 814482
7.9%
9 682550
 
6.6%
Other values (29) 85913
 
0.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10311762
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1932130
18.7%
4 1082823
10.5%
1 1062075
10.3%
5 1038144
10.1%
3 1034312
10.0%
2 876562
8.5%
7 861219
8.4%
6 841552
8.2%
8 814482
7.9%
9 682550
 
6.6%
Other values (29) 85913
 
0.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10311762
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1932130
18.7%
4 1082823
10.5%
1 1062075
10.3%
5 1038144
10.1%
3 1034312
10.0%
2 876562
8.5%
7 861219
8.4%
6 841552
8.2%
8 814482
7.9%
9 682550
 
6.6%
Other values (29) 85913
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10311762
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1932130
18.7%
4 1082823
10.5%
1 1062075
10.3%
5 1038144
10.1%
3 1034312
10.0%
2 876562
8.5%
7 861219
8.4%
6 841552
8.2%
8 814482
7.9%
9 682550
 
6.6%
Other values (29) 85913
 
0.8%

rating
Real number (ℝ)

Zeros 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8390215
Minimum0
Maximum10
Zeros647323
Zeros (%)62.8%
Negative0
Negative (%)0.0%
Memory size7.9 MiB
2025-02-26T11:14:31.357639image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile10
Maximum10
Range10
Interquartile range (IQR)7

Descriptive statistics

Standard deviation3.8541492
Coefficient of variation (CV)1.3575625
Kurtosis-1.2150103
Mean2.8390215
Median Absolute Deviation (MAD)0
Skewness0.75243535
Sum2927528
Variance14.854466
MonotonicityNot monotonic
2025-02-26T11:14:31.505611image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
0 647323
62.8%
8 91806
 
8.9%
10 71227
 
6.9%
7 66404
 
6.4%
9 60780
 
5.9%
5 45355
 
4.4%
6 31689
 
3.1%
4 7617
 
0.7%
3 5118
 
0.5%
2 2375
 
0.2%
ValueCountFrequency (%)
0 647323
62.8%
1 1481
 
0.1%
2 2375
 
0.2%
3 5118
 
0.5%
4 7617
 
0.7%
5 45355
 
4.4%
6 31689
 
3.1%
7 66404
 
6.4%
8 91806
 
8.9%
9 60780
 
5.9%
ValueCountFrequency (%)
10 71227
6.9%
9 60780
5.9%
8 91806
8.9%
7 66404
6.4%
6 31689
 
3.1%
5 45355
4.4%
4 7617
 
0.7%
3 5118
 
0.5%
2 2375
 
0.2%
1 1481
 
0.1%
Distinct241090
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size89.1 MiB
2025-02-26T11:14:31.851255image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length256
Median length211
Mean length32.71261
Min length1

Characters and Unicode

Total characters33732426
Distinct characters126
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique127524 ?
Unique (%)12.4%

Sample

1st rowClassical Mythology
2nd rowClara Callan
3rd rowClara Callan
4th rowClara Callan
5th rowClara Callan
ValueCountFrequency (%)
the 461771
 
8.2%
of 220678
 
3.9%
a 174061
 
3.1%
and 100167
 
1.8%
85788
 
1.5%
in 63123
 
1.1%
to 60517
 
1.1%
novel 54387
 
1.0%
book 46932
 
0.8%
for 41821
 
0.7%
Other values (93219) 4296248
76.6%
2025-02-26T11:14:32.422291image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4585156
 
13.6%
e 3228366
 
9.6%
o 1999873
 
5.9%
a 1855355
 
5.5%
r 1765522
 
5.2%
i 1721233
 
5.1%
n 1681241
 
5.0%
t 1557566
 
4.6%
s 1387806
 
4.1%
l 1084723
 
3.2%
Other values (116) 12865585
38.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 33732426
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4585156
 
13.6%
e 3228366
 
9.6%
o 1999873
 
5.9%
a 1855355
 
5.5%
r 1765522
 
5.2%
i 1721233
 
5.1%
n 1681241
 
5.0%
t 1557566
 
4.6%
s 1387806
 
4.1%
l 1084723
 
3.2%
Other values (116) 12865585
38.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 33732426
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4585156
 
13.6%
e 3228366
 
9.6%
o 1999873
 
5.9%
a 1855355
 
5.5%
r 1765522
 
5.2%
i 1721233
 
5.1%
n 1681241
 
5.0%
t 1557566
 
4.6%
s 1387806
 
4.1%
l 1084723
 
3.2%
Other values (116) 12865585
38.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 33732426
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4585156
 
13.6%
e 3228366
 
9.6%
o 1999873
 
5.9%
a 1855355
 
5.5%
r 1765522
 
5.2%
i 1721233
 
5.1%
n 1681241
 
5.0%
t 1557566
 
4.6%
s 1387806
 
4.1%
l 1084723
 
3.2%
Other values (116) 12865585
38.1%
Distinct101593
Distinct (%)9.9%
Missing1
Missing (%)< 0.1%
Memory size69.7 MiB
2025-02-26T11:14:32.782206image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length143
Median length70
Mean length13.751096
Min length1

Characters and Unicode

Total characters14179773
Distinct characters109
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique49280 ?
Unique (%)4.8%

Sample

1st rowMark P. O. Morford
2nd rowRichard Bruce Wright
3rd rowRichard Bruce Wright
4th rowRichard Bruce Wright
5th rowRichard Bruce Wright
ValueCountFrequency (%)
john 32558
 
1.4%
james 20384
 
0.9%
robert 18457
 
0.8%
michael 16959
 
0.8%
stephen 16524
 
0.7%
r 15345
 
0.7%
david 14916
 
0.7%
j 14678
 
0.6%
anne 14218
 
0.6%
mary 12185
 
0.5%
Other values (49131) 2082249
92.2%
2025-02-26T11:14:33.603534image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1263261
 
8.9%
1230224
 
8.7%
a 1160642
 
8.2%
n 967461
 
6.8%
r 933572
 
6.6%
i 769864
 
5.4%
o 690693
 
4.9%
l 668913
 
4.7%
t 497532
 
3.5%
s 459031
 
3.2%
Other values (99) 5538580
39.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14179773
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 1263261
 
8.9%
1230224
 
8.7%
a 1160642
 
8.2%
n 967461
 
6.8%
r 933572
 
6.6%
i 769864
 
5.4%
o 690693
 
4.9%
l 668913
 
4.7%
t 497532
 
3.5%
s 459031
 
3.2%
Other values (99) 5538580
39.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14179773
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 1263261
 
8.9%
1230224
 
8.7%
a 1160642
 
8.2%
n 967461
 
6.8%
r 933572
 
6.6%
i 769864
 
5.4%
o 690693
 
4.9%
l 668913
 
4.7%
t 497532
 
3.5%
s 459031
 
3.2%
Other values (99) 5538580
39.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14179773
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 1263261
 
8.9%
1230224
 
8.7%
a 1160642
 
8.2%
n 967461
 
6.8%
r 933572
 
6.6%
i 769864
 
5.4%
o 690693
 
4.9%
l 668913
 
4.7%
t 497532
 
3.5%
s 459031
 
3.2%
Other values (99) 5538580
39.1%

year_of_publication
Real number (ℝ)

Distinct104
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1995.2827
Minimum1376
Maximum2008
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size7.9 MiB
2025-02-26T11:14:33.777560image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1376
5-th percentile1982
Q11992
median1997
Q32001
95-th percentile2003
Maximum2008
Range632
Interquartile range (IQR)9

Descriptive statistics

Standard deviation7.3093401
Coefficient of variation (CV)0.0036633106
Kurtosis107.24842
Mean1995.2827
Median Absolute Deviation (MAD)4
Skewness-3.0531031
Sum2.0574856 × 109
Variance53.426453
MonotonicityNot monotonic
2025-02-26T11:14:33.950932image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2002 91801
 
8.9%
2001 79803
 
7.7%
1999 75195
 
7.3%
2003 72539
 
7.0%
2000 72334
 
7.0%
1998 64209
 
6.2%
1994 60533
 
5.9%
1997 59361
 
5.8%
1996 58826
 
5.7%
1995 54093
 
5.2%
Other values (94) 342481
33.2%
ValueCountFrequency (%)
1376 1
 
< 0.1%
1378 1
 
< 0.1%
1806 1
 
< 0.1%
1897 1
 
< 0.1%
1900 4
 
< 0.1%
1901 7
< 0.1%
1902 10
< 0.1%
1904 1
 
< 0.1%
1906 1
 
< 0.1%
1908 3
 
< 0.1%
ValueCountFrequency (%)
2008 1
 
< 0.1%
2006 3
 
< 0.1%
2005 122
 
< 0.1%
2004 25971
 
2.5%
2003 72539
7.0%
2002 91801
8.9%
2001 79803
7.7%
2000 72334
7.0%
1999 75195
7.3%
1998 64209
6.2%
Distinct16729
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size70.0 MiB
2025-02-26T11:14:34.218680image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length134
Median length88
Mean length14.088498
Min length1

Characters and Unicode

Total characters14527707
Distinct characters115
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7153 ?
Unique (%)0.7%

Sample

1st rowOxford University Press
2nd rowHarperFlamingo Canada
3rd rowHarperFlamingo Canada
4th rowHarperFlamingo Canada
5th rowHarperFlamingo Canada
ValueCountFrequency (%)
books 289588
 
13.3%
publishing 74377
 
3.4%
bantam 53309
 
2.4%
press 51201
 
2.4%
group 49822
 
2.3%
39280
 
1.8%
pocket 38651
 
1.8%
dell 35068
 
1.6%
ballantine 34864
 
1.6%
warner 33717
 
1.5%
Other values (11400) 1478364
67.9%
2025-02-26T11:14:34.697319image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 1312896
 
9.0%
1147070
 
7.9%
e 1061244
 
7.3%
n 930394
 
6.4%
a 895126
 
6.2%
r 884118
 
6.1%
s 852276
 
5.9%
i 784350
 
5.4%
l 657268
 
4.5%
t 589550
 
4.1%
Other values (105) 5413415
37.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14527707
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 1312896
 
9.0%
1147070
 
7.9%
e 1061244
 
7.3%
n 930394
 
6.4%
a 895126
 
6.2%
r 884118
 
6.1%
s 852276
 
5.9%
i 784350
 
5.4%
l 657268
 
4.5%
t 589550
 
4.1%
Other values (105) 5413415
37.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14527707
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 1312896
 
9.0%
1147070
 
7.9%
e 1061244
 
7.3%
n 930394
 
6.4%
a 895126
 
6.2%
r 884118
 
6.1%
s 852276
 
5.9%
i 784350
 
5.4%
l 657268
 
4.5%
t 589550
 
4.1%
Other values (105) 5413415
37.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14527707
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 1312896
 
9.0%
1147070
 
7.9%
e 1061244
 
7.3%
n 930394
 
6.4%
a 895126
 
6.2%
r 884118
 
6.1%
s 852276
 
5.9%
i 784350
 
5.4%
l 657268
 
4.5%
t 589550
 
4.1%
Other values (105) 5413415
37.3%
Distinct269861
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size115.1 MiB
http://images.amazon.com/images/P/0971880107.01.THUMBZZZ.jpg
 
2502
http://images.amazon.com/images/P/0316666343.01.THUMBZZZ.jpg
 
1295
http://images.amazon.com/images/P/0385504209.01.THUMBZZZ.jpg
 
883
http://images.amazon.com/images/P/0060928336.01.THUMBZZZ.jpg
 
732
http://images.amazon.com/images/P/0312195516.01.THUMBZZZ.jpg
 
723
Other values (269856)
1025040 
ValueCountFrequency (%)
http://images.amazon.com/images/P/0971880107.01.THUMBZZZ.jpg 2502
 
0.2%
http://images.amazon.com/images/P/0316666343.01.THUMBZZZ.jpg 1295
 
0.1%
http://images.amazon.com/images/P/0385504209.01.THUMBZZZ.jpg 883
 
0.1%
http://images.amazon.com/images/P/0060928336.01.THUMBZZZ.jpg 732
 
0.1%
http://images.amazon.com/images/P/0312195516.01.THUMBZZZ.jpg 723
 
0.1%
http://images.amazon.com/images/P/044023722X.01.THUMBZZZ.jpg 649
 
0.1%
http://images.amazon.com/images/P/067976402X.01.THUMBZZZ.jpg 618
 
0.1%
http://images.amazon.com/images/P/0142001740.01.THUMBZZZ.jpg 615
 
0.1%
http://images.amazon.com/images/P/0671027360.01.THUMBZZZ.jpg 586
 
0.1%
http://images.amazon.com/images/P/0446672211.01.THUMBZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
http 1031175
100.0%
ValueCountFrequency (%)
images.amazon.com 1031175
100.0%
ValueCountFrequency (%)
/images/P/0971880107.01.THUMBZZZ.jpg 2502
 
0.2%
/images/P/0316666343.01.THUMBZZZ.jpg 1295
 
0.1%
/images/P/0385504209.01.THUMBZZZ.jpg 883
 
0.1%
/images/P/0060928336.01.THUMBZZZ.jpg 732
 
0.1%
/images/P/0312195516.01.THUMBZZZ.jpg 723
 
0.1%
/images/P/044023722X.01.THUMBZZZ.jpg 649
 
0.1%
/images/P/067976402X.01.THUMBZZZ.jpg 618
 
0.1%
/images/P/0142001740.01.THUMBZZZ.jpg 615
 
0.1%
/images/P/0671027360.01.THUMBZZZ.jpg 586
 
0.1%
/images/P/0446672211.01.THUMBZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
1031175
100.0%
ValueCountFrequency (%)
1031175
100.0%
Distinct269861
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size115.1 MiB
http://images.amazon.com/images/P/0971880107.01.MZZZZZZZ.jpg
 
2502
http://images.amazon.com/images/P/0316666343.01.MZZZZZZZ.jpg
 
1295
http://images.amazon.com/images/P/0385504209.01.MZZZZZZZ.jpg
 
883
http://images.amazon.com/images/P/0060928336.01.MZZZZZZZ.jpg
 
732
http://images.amazon.com/images/P/0312195516.01.MZZZZZZZ.jpg
 
723
Other values (269856)
1025040 
ValueCountFrequency (%)
http://images.amazon.com/images/P/0971880107.01.MZZZZZZZ.jpg 2502
 
0.2%
http://images.amazon.com/images/P/0316666343.01.MZZZZZZZ.jpg 1295
 
0.1%
http://images.amazon.com/images/P/0385504209.01.MZZZZZZZ.jpg 883
 
0.1%
http://images.amazon.com/images/P/0060928336.01.MZZZZZZZ.jpg 732
 
0.1%
http://images.amazon.com/images/P/0312195516.01.MZZZZZZZ.jpg 723
 
0.1%
http://images.amazon.com/images/P/044023722X.01.MZZZZZZZ.jpg 649
 
0.1%
http://images.amazon.com/images/P/067976402X.01.MZZZZZZZ.jpg 618
 
0.1%
http://images.amazon.com/images/P/0142001740.01.MZZZZZZZ.jpg 615
 
0.1%
http://images.amazon.com/images/P/0671027360.01.MZZZZZZZ.jpg 586
 
0.1%
http://images.amazon.com/images/P/0446672211.01.MZZZZZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
http 1031175
100.0%
ValueCountFrequency (%)
images.amazon.com 1031175
100.0%
ValueCountFrequency (%)
/images/P/0971880107.01.MZZZZZZZ.jpg 2502
 
0.2%
/images/P/0316666343.01.MZZZZZZZ.jpg 1295
 
0.1%
/images/P/0385504209.01.MZZZZZZZ.jpg 883
 
0.1%
/images/P/0060928336.01.MZZZZZZZ.jpg 732
 
0.1%
/images/P/0312195516.01.MZZZZZZZ.jpg 723
 
0.1%
/images/P/044023722X.01.MZZZZZZZ.jpg 649
 
0.1%
/images/P/067976402X.01.MZZZZZZZ.jpg 618
 
0.1%
/images/P/0142001740.01.MZZZZZZZ.jpg 615
 
0.1%
/images/P/0671027360.01.MZZZZZZZ.jpg 586
 
0.1%
/images/P/0446672211.01.MZZZZZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
1031175
100.0%
ValueCountFrequency (%)
1031175
100.0%
Distinct269861
Distinct (%)26.2%
Missing0
Missing (%)0.0%
Memory size115.1 MiB
http://images.amazon.com/images/P/0971880107.01.LZZZZZZZ.jpg
 
2502
http://images.amazon.com/images/P/0316666343.01.LZZZZZZZ.jpg
 
1295
http://images.amazon.com/images/P/0385504209.01.LZZZZZZZ.jpg
 
883
http://images.amazon.com/images/P/0060928336.01.LZZZZZZZ.jpg
 
732
http://images.amazon.com/images/P/0312195516.01.LZZZZZZZ.jpg
 
723
Other values (269856)
1025040 
ValueCountFrequency (%)
http://images.amazon.com/images/P/0971880107.01.LZZZZZZZ.jpg 2502
 
0.2%
http://images.amazon.com/images/P/0316666343.01.LZZZZZZZ.jpg 1295
 
0.1%
http://images.amazon.com/images/P/0385504209.01.LZZZZZZZ.jpg 883
 
0.1%
http://images.amazon.com/images/P/0060928336.01.LZZZZZZZ.jpg 732
 
0.1%
http://images.amazon.com/images/P/0312195516.01.LZZZZZZZ.jpg 723
 
0.1%
http://images.amazon.com/images/P/044023722X.01.LZZZZZZZ.jpg 649
 
0.1%
http://images.amazon.com/images/P/067976402X.01.LZZZZZZZ.jpg 618
 
0.1%
http://images.amazon.com/images/P/0142001740.01.LZZZZZZZ.jpg 615
 
0.1%
http://images.amazon.com/images/P/0671027360.01.LZZZZZZZ.jpg 586
 
0.1%
http://images.amazon.com/images/P/0446672211.01.LZZZZZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
http 1031175
100.0%
ValueCountFrequency (%)
images.amazon.com 1031175
100.0%
ValueCountFrequency (%)
/images/P/0971880107.01.LZZZZZZZ.jpg 2502
 
0.2%
/images/P/0316666343.01.LZZZZZZZ.jpg 1295
 
0.1%
/images/P/0385504209.01.LZZZZZZZ.jpg 883
 
0.1%
/images/P/0060928336.01.LZZZZZZZ.jpg 732
 
0.1%
/images/P/0312195516.01.LZZZZZZZ.jpg 723
 
0.1%
/images/P/044023722X.01.LZZZZZZZ.jpg 649
 
0.1%
/images/P/067976402X.01.LZZZZZZZ.jpg 618
 
0.1%
/images/P/0142001740.01.LZZZZZZZ.jpg 615
 
0.1%
/images/P/0671027360.01.LZZZZZZZ.jpg 586
 
0.1%
/images/P/0446672211.01.LZZZZZZZ.jpg 585
 
0.1%
Other values (269851) 1021987
99.1%
ValueCountFrequency (%)
1031175
100.0%
ValueCountFrequency (%)
1031175
100.0%
Distinct136911
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size169.9 MiB
2025-02-26T11:14:35.116310image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length374
Median length297
Mean length109.08555
Min length1

Characters and Unicode

Total characters112486297
Distinct characters466
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique66037 ?
Unique (%)6.4%

Sample

1st rowProvides an introduction to classical myths placing the addressed topics within their historical context, discussion of archaeological evidence as support for mythical events, and how these themes have been portrayed in literature, art, ...
2nd rowIn a small town in Canada, Clara Callan reluctantly takes leave of her sister, Nora, who is bound for New York.
3rd rowIn a small town in Canada, Clara Callan reluctantly takes leave of her sister, Nora, who is bound for New York.
4th rowIn a small town in Canada, Clara Callan reluctantly takes leave of her sister, Nora, who is bound for New York.
5th rowIn a small town in Canada, Clara Callan reluctantly takes leave of her sister, Nora, who is bound for New York.
ValueCountFrequency (%)
the 1041929
 
5.6%
of 713907
 
3.8%
a 698979
 
3.8%
and 631892
 
3.4%
to 429704
 
2.3%
9 399202
 
2.2%
in 345630
 
1.9%
her 226898
 
1.2%
is 210285
 
1.1%
for 162808
 
0.9%
Other values (155678) 13681897
73.8%
2025-02-26T11:14:35.738134image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
16187576
14.4%
e 10716585
 
9.5%
a 7205834
 
6.4%
t 7065437
 
6.3%
n 6550881
 
5.8%
i 6532615
 
5.8%
o 6526239
 
5.8%
r 6122476
 
5.4%
s 5904740
 
5.2%
h 4278200
 
3.8%
Other values (456) 35395714
31.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 112486297
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
16187576
14.4%
e 10716585
 
9.5%
a 7205834
 
6.4%
t 7065437
 
6.3%
n 6550881
 
5.8%
i 6532615
 
5.8%
o 6526239
 
5.8%
r 6122476
 
5.4%
s 5904740
 
5.2%
h 4278200
 
3.8%
Other values (456) 35395714
31.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 112486297
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
16187576
14.4%
e 10716585
 
9.5%
a 7205834
 
6.4%
t 7065437
 
6.3%
n 6550881
 
5.8%
i 6532615
 
5.8%
o 6526239
 
5.8%
r 6122476
 
5.4%
s 5904740
 
5.2%
h 4278200
 
3.8%
Other values (456) 35395714
31.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 112486297
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
16187576
14.4%
e 10716585
 
9.5%
a 7205834
 
6.4%
t 7065437
 
6.3%
n 6550881
 
5.8%
i 6532615
 
5.8%
o 6526239
 
5.8%
r 6122476
 
5.4%
s 5904740
 
5.2%
h 4278200
 
3.8%
Other values (456) 35395714
31.5%

Language
Categorical

Imbalance 

Distinct33
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size57.6 MiB
en
618505 
9
398937 
de
 
5725
es
 
3425
fr
 
3223
Other values (28)
 
1360

Length

Max length5
Median length2
Mean length1.6131559
Min length1

Characters and Unicode

Total characters1663446
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowen
2nd rowen
3rd rowen
4th rowen
5th rowen

Common Values

ValueCountFrequency (%)
en 618505
60.0%
9 398937
38.7%
de 5725
 
0.6%
es 3425
 
0.3%
fr 3223
 
0.3%
it 732
 
0.1%
nl 238
 
< 0.1%
da 119
 
< 0.1%
pt 100
 
< 0.1%
ca 49
 
< 0.1%
Other values (23) 122
 
< 0.1%

Length

2025-02-26T11:14:35.922501image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
en 618505
60.0%
9 398937
38.7%
de 5725
 
0.6%
es 3425
 
0.3%
fr 3223
 
0.3%
it 732
 
0.1%
nl 238
 
< 0.1%
da 119
 
< 0.1%
pt 100
 
< 0.1%
ca 49
 
< 0.1%
Other values (23) 122
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 627663
37.7%
n 618756
37.2%
9 398937
24.0%
d 5846
 
0.4%
s 3437
 
0.2%
r 3251
 
0.2%
f 3225
 
0.2%
t 839
 
0.1%
i 736
 
< 0.1%
l 268
 
< 0.1%
Other values (18) 488
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1663446
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 627663
37.7%
n 618756
37.2%
9 398937
24.0%
d 5846
 
0.4%
s 3437
 
0.2%
r 3251
 
0.2%
f 3225
 
0.2%
t 839
 
0.1%
i 736
 
< 0.1%
l 268
 
< 0.1%
Other values (18) 488
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1663446
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 627663
37.7%
n 618756
37.2%
9 398937
24.0%
d 5846
 
0.4%
s 3437
 
0.2%
r 3251
 
0.2%
f 3225
 
0.2%
t 839
 
0.1%
i 736
 
< 0.1%
l 268
 
< 0.1%
Other values (18) 488
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1663446
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 627663
37.7%
n 618756
37.2%
9 398937
24.0%
d 5846
 
0.4%
s 3437
 
0.2%
r 3251
 
0.2%
f 3225
 
0.2%
t 839
 
0.1%
i 736
 
< 0.1%
l 268
 
< 0.1%
Other values (18) 488
 
< 0.1%
Distinct6448
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size64.8 MiB
2025-02-26T11:14:36.206928image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length279
Median length118
Mean length8.9121536
Min length1

Characters and Unicode

Total characters9189990
Distinct characters112
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2426 ?
Unique (%)0.2%

Sample

1st row['Social Science']
2nd row['Actresses']
3rd row['Actresses']
4th row['Actresses']
5th row['Actresses']
ValueCountFrequency (%)
fiction 433139
34.1%
9 406102
32.0%
48094
 
3.8%
juvenile 45410
 
3.6%
biography 22621
 
1.8%
autobiography 22549
 
1.8%
science 10079
 
0.8%
humor 9028
 
0.7%
history 8520
 
0.7%
religion 7307
 
0.6%
Other values (5677) 256601
20.2%
2025-02-26T11:14:36.689493image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
' 1248035
13.6%
i 1170814
12.7%
o 652437
 
7.1%
[ 625074
 
6.8%
] 625074
 
6.8%
n 614275
 
6.7%
t 583967
 
6.4%
c 530396
 
5.8%
F 443764
 
4.8%
9 406985
 
4.4%
Other values (102) 2289169
24.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9189990
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
' 1248035
13.6%
i 1170814
12.7%
o 652437
 
7.1%
[ 625074
 
6.8%
] 625074
 
6.8%
n 614275
 
6.7%
t 583967
 
6.4%
c 530396
 
5.8%
F 443764
 
4.8%
9 406985
 
4.4%
Other values (102) 2289169
24.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9189990
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
' 1248035
13.6%
i 1170814
12.7%
o 652437
 
7.1%
[ 625074
 
6.8%
] 625074
 
6.8%
n 614275
 
6.7%
t 583967
 
6.4%
c 530396
 
5.8%
F 443764
 
4.8%
9 406985
 
4.4%
Other values (102) 2289169
24.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9189990
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
' 1248035
13.6%
i 1170814
12.7%
o 652437
 
7.1%
[ 625074
 
6.8%
] 625074
 
6.8%
n 614275
 
6.7%
t 583967
 
6.4%
c 530396
 
5.8%
F 443764
 
4.8%
9 406985
 
4.4%
Other values (102) 2289169
24.9%

city
Text

Missing 

Distinct14767
Distinct (%)1.5%
Missing14103
Missing (%)1.4%
Memory size64.4 MiB
2025-02-26T11:14:36.984573image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length47
Median length37
Mean length8.7001314
Min length1

Characters and Unicode

Total characters8848660
Distinct characters84
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4855 ?
Unique (%)0.5%

Sample

1st rowstockton
2nd rowtimmins
3rd rowottawa
4th rowsudbury
5th rowtoronto
ValueCountFrequency (%)
san 22513
 
1.8%
st 17816
 
1.4%
city 15594
 
1.2%
toronto 15124
 
1.2%
louis 13628
 
1.1%
new 11591
 
0.9%
beach 11030
 
0.9%
chicago 9418
 
0.7%
ft 9224
 
0.7%
little 8617
 
0.7%
Other values (12983) 1146436
89.5%
2025-02-26T11:14:37.447554image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 878949
 
9.9%
e 774237
 
8.7%
o 748122
 
8.5%
n 703817
 
8.0%
l 637878
 
7.2%
r 608874
 
6.9%
i 550374
 
6.2%
t 528345
 
6.0%
s 502627
 
5.7%
c 314316
 
3.6%
Other values (74) 2601121
29.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8848660
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 878949
 
9.9%
e 774237
 
8.7%
o 748122
 
8.5%
n 703817
 
8.0%
l 637878
 
7.2%
r 608874
 
6.9%
i 550374
 
6.2%
t 528345
 
6.0%
s 502627
 
5.7%
c 314316
 
3.6%
Other values (74) 2601121
29.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8848660
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 878949
 
9.9%
e 774237
 
8.7%
o 748122
 
8.5%
n 703817
 
8.0%
l 637878
 
7.2%
r 608874
 
6.9%
i 550374
 
6.2%
t 528345
 
6.0%
s 502627
 
5.7%
c 314316
 
3.6%
Other values (74) 2601121
29.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8848660
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 878949
 
9.9%
e 774237
 
8.7%
o 748122
 
8.5%
n 703817
 
8.0%
l 637878
 
7.2%
r 608874
 
6.9%
i 550374
 
6.2%
t 528345
 
6.0%
s 502627
 
5.7%
c 314316
 
3.6%
Other values (74) 2601121
29.4%

state
Text

Missing 

Distinct2123
Distinct (%)0.2%
Missing22798
Missing (%)2.2%
Memory size64.1 MiB
2025-02-26T11:14:37.726878image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length49
Median length37
Mean length8.6172324
Min length1

Characters and Unicode

Total characters8689419
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique767 ?
Unique (%)0.1%

Sample

1st rowcalifornia
2nd rowontario
3rd rowontario
4th rowontario
5th rowontario
ValueCountFrequency (%)
california 107500
 
9.2%
new 69766
 
6.0%
texas 44173
 
3.8%
ontario 41455
 
3.5%
virginia 34999
 
3.0%
florida 34258
 
2.9%
missouri 33007
 
2.8%
washington 31956
 
2.7%
illinois 30626
 
2.6%
york 29790
 
2.5%
Other values (1913) 713273
60.9%
2025-02-26T11:14:38.200108image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1136556
13.1%
i 1017765
11.7%
n 899518
10.4%
o 753906
 
8.7%
r 611153
 
7.0%
e 565023
 
6.5%
s 546331
 
6.3%
l 444416
 
5.1%
t 376764
 
4.3%
c 309364
 
3.6%
Other values (69) 2028623
23.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8689419
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1136556
13.1%
i 1017765
11.7%
n 899518
10.4%
o 753906
 
8.7%
r 611153
 
7.0%
e 565023
 
6.5%
s 546331
 
6.3%
l 444416
 
5.1%
t 376764
 
4.3%
c 309364
 
3.6%
Other values (69) 2028623
23.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8689419
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1136556
13.1%
i 1017765
11.7%
n 899518
10.4%
o 753906
 
8.7%
r 611153
 
7.0%
e 565023
 
6.5%
s 546331
 
6.3%
l 444416
 
5.1%
t 376764
 
4.3%
c 309364
 
3.6%
Other values (69) 2028623
23.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8689419
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1136556
13.1%
i 1017765
11.7%
n 899518
10.4%
o 753906
 
8.7%
r 611153
 
7.0%
e 565023
 
6.5%
s 546331
 
6.3%
l 444416
 
5.1%
t 376764
 
4.3%
c 309364
 
3.6%
Other values (69) 2028623
23.3%

country
Text

Missing 

Distinct414
Distinct (%)< 0.1%
Missing35374
Missing (%)3.4%
Memory size59.2 MiB
2025-02-26T11:14:38.483413image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length43
Median length3
Mean length4.2359548
Min length1

Characters and Unicode

Total characters4218168
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)< 0.1%

Sample

1st rowusa
2nd rowcanada
3rd rowcanada
4th rowcanada
5th rowcanada
ValueCountFrequency (%)
usa 746518
71.8%
canada 93005
 
8.9%
united 33346
 
3.2%
kingdom 33078
 
3.2%
germany 27665
 
2.7%
australia 18239
 
1.8%
spain 14989
 
1.4%
france 10658
 
1.0%
portugal 6984
 
0.7%
new 5968
 
0.6%
Other values (405) 49849
 
4.8%
2025-02-26T11:14:38.936177image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1206904
28.6%
u 811861
19.2%
s 802584
19.0%
n 257087
 
6.1%
d 180767
 
4.3%
i 133129
 
3.2%
e 109059
 
2.6%
c 108524
 
2.6%
r 87496
 
2.1%
t 76864
 
1.8%
Other values (43) 443893
 
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4218168
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1206904
28.6%
u 811861
19.2%
s 802584
19.0%
n 257087
 
6.1%
d 180767
 
4.3%
i 133129
 
3.2%
e 109059
 
2.6%
c 108524
 
2.6%
r 87496
 
2.1%
t 76864
 
1.8%
Other values (43) 443893
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4218168
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1206904
28.6%
u 811861
19.2%
s 802584
19.0%
n 257087
 
6.1%
d 180767
 
4.3%
i 133129
 
3.2%
e 109059
 
2.6%
c 108524
 
2.6%
r 87496
 
2.1%
t 76864
 
1.8%
Other values (43) 443893
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4218168
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1206904
28.6%
u 811861
19.2%
s 802584
19.0%
n 257087
 
6.1%
d 180767
 
4.3%
i 133129
 
3.2%
e 109059
 
2.6%
c 108524
 
2.6%
r 87496
 
2.1%
t 76864
 
1.8%
Other values (43) 443893
 
10.5%

Interactions

2025-02-26T11:14:20.609688image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:16.066519image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:17.209408image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:18.411348image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:19.489084image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:20.829123image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:16.364101image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:17.422271image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:18.644592image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:19.715370image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:21.052052image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:16.566636image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:17.647830image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:18.858467image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:19.936919image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:21.247641image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:16.778073image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:17.901785image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:19.057970image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:20.155614image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:21.442893image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:16.990990image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:18.152985image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:19.277418image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2025-02-26T11:14:20.382910image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Correlations

2025-02-26T11:14:39.058121image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
LanguageUnnamed: 0ageratinguser_idyear_of_publication
Language1.0000.0410.0190.0130.0110.289
Unnamed: 00.0411.0000.039-0.0420.170-0.158
age0.0190.0391.000-0.018-0.013-0.009
rating0.013-0.042-0.0181.000-0.0440.052
user_id0.0110.170-0.013-0.0441.000-0.013
year_of_publication0.289-0.158-0.0090.052-0.0131.000

Missing values

2025-02-26T11:14:22.104810image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2025-02-26T11:14:23.955871image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2025-02-26T11:14:26.802729image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

Unnamed: 0user_idlocationageisbnratingbook_titlebook_authoryear_of_publicationpublisherimg_simg_mimg_lSummaryLanguageCategorycitystatecountry
002stockton, california, usa18.000001951534480Classical MythologyMark P. O. Morford2002.0Oxford University Presshttp://images.amazon.com/images/P/0195153448.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0195153448.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0195153448.01.LZZZZZZZ.jpgProvides an introduction to classical myths placing the addressed\ntopics within their historical context, discussion of archaeological\nevidence as support for mythical events, and how these themes have\nbeen portrayed in literature, art, ...en['Social Science']stocktoncaliforniausa
118timmins, ontario, canada34.743900020050185Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']timminsontariocanada
2211400ottawa, ontario, canada49.000000020050180Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']ottawaontariocanada
3311676n/a, n/a, n/a34.743900020050188Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']NaNNaNNaN
4441385sudbury, ontario, canada34.743900020050180Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']sudburyontariocanada
5567544toronto, ontario, canada30.000000020050188Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']torontoontariocanada
6685526victoria, british columbia, canada36.000000020050180Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']victoriabritish columbiacanada
7796054ottawa, ontario, canada29.000000020050180Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']ottawaontariocanada
88116866ottawa, ,34.743900020050189Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']ottawa,NaN
99123629kingston, ontario, canada34.743900020050189Clara CallanRichard Bruce Wright2001.0HarperFlamingo Canadahttp://images.amazon.com/images/P/0002005018.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0002005018.01.LZZZZZZZ.jpgIn a small town in Canada, Clara Callan reluctantly takes leave of her\nsister, Nora, who is bound for New York.en['Actresses']kingstonontariocanada
Unnamed: 0user_idlocationageisbnratingbook_titlebook_authoryear_of_publicationpublisherimg_simg_mimg_lSummaryLanguageCategorycitystatecountry
10311651031165278843pismo beach, california, usa28.018740611490The Queen's GambitWalter Tevis1996.0Texas Bookmanhttp://images.amazon.com/images/P/1874061149.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/1874061149.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/1874061149.01.LZZZZZZZ.jpgEngaging and fast-paced, The Queen&#39;s Gambit speeds to a conclusion\nas elegant and satisfying as a mate in four.en['Fiction']pismo beachcaliforniausa
10311661031166278849georgetown, ontario, canada23.009206563070Secret of Willow CastleLy Cook1911.0Firefly Books Ltdhttp://images.amazon.com/images/P/0920656307.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0920656307.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0920656307.01.LZZZZZZZ.jpgCanadian story early 19th century Orphaned servant girl sent to farm.en['Canada']georgetownontariocanada
10311671031167278851dallas, texas, usa33.000286302890Frommer's 2000 California (Frommer's California 2000)Erika Lenkert1999.0Frommer'shttp://images.amazon.com/images/P/0028630289.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0028630289.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0028630289.01.LZZZZZZZ.jpg999dallastexasusa
10311681031168278851dallas, texas, usa33.003122664480The Military Quotation Book : Revised and Expanded: More than 1,200 of the Best Quotations About War, Leadership, Courage, Victory, and DefeatJames Charlton2002.0Thomas Dunne Bookshttp://images.amazon.com/images/P/0312266448.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0312266448.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0312266448.01.LZZZZZZZ.jpgContains more than 1,200 quotations about war, courage, combat,\nvictory, and defeat, by such people as Charles Dickens, George Patton,\nWinston Churchill, Voltaire, and Colin Powell.en['Reference']dallastexasusa
10311691031169278851dallas, texas, usa33.0067161746X7The Bachelor Home Companion: A Practical Guide to Keeping House Like a PigP.J. O'Rourke1987.0Pocket Bookshttp://images.amazon.com/images/P/067161746X.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/067161746X.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/067161746X.01.LZZZZZZZ.jpgA tongue-in-cheek survival guide for single people reveals the\nquintessential secrets of no-fuss housekeepingen['Humor']dallastexasusa
10311701031170278851dallas, texas, usa33.007432037630As Hogan Said . . . : The 389 Best Things Anyone Said about How to Play GolfRandy Voorhees2000.0Simon & Schusterhttp://images.amazon.com/images/P/0743203763.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0743203763.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0743203763.01.LZZZZZZZ.jpgGolf lovers will revel in this collection of tips, wisdom, and\nquotations culled from the masters of the game, including Bobby Jones,\nJack Nichlaus, Sam Snead, Tom Watson, and Tiger Woods. 60,000 first\nprinting.en['Humor']dallastexasusa
10311711031171278851dallas, texas, usa33.007679075665All Elevations Unknown: An Adventure in the Heart of BorneoSam Lightner2001.0Broadway Bookshttp://images.amazon.com/images/P/0767907566.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0767907566.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0767907566.01.LZZZZZZZ.jpgA daring twist on the travel-adventure genre that places the talented\nLightner in the ranks of authors such as Jon Krakauer, Sebastian\nJunger, and Redmond O&#39;Hanlon, All Elevations Unknown is ultimately\nthe remarkable story of two ...en['Nature']dallastexasusa
10311721031172278851dallas, texas, usa33.008841592217Why stop?: A guide to Texas historical roadside markersClaude Dooley1985.0Lone Star Bookshttp://images.amazon.com/images/P/0884159221.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0884159221.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0884159221.01.LZZZZZZZ.jpg999dallastexasusa
10311731031173278851dallas, texas, usa33.009123330227The Are You Being Served? Stories: 'Camping In' and Other FiascoesJeremy Lloyd1997.0Kqed Bookshttp://images.amazon.com/images/P/0912333022.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/0912333022.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/0912333022.01.LZZZZZZZ.jpgThese hilarious stories by the creator of public television&#39;s\nlongest-running hit series capture the wacky sensibility and off-the-\nwall humor of the British sitcom.en['Fiction']dallastexasusa
10311741031174278851dallas, texas, usa33.0156966105710Dallas Street Map Guide and Directory, 2000 EditionMapsco1999.0American Map Corporationhttp://images.amazon.com/images/P/1569661057.01.THUMBZZZ.jpghttp://images.amazon.com/images/P/1569661057.01.MZZZZZZZ.jpghttp://images.amazon.com/images/P/1569661057.01.LZZZZZZZ.jpg999dallastexasusa